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Title |
Crowdsourcing Based on Clustering |
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Author |
Sheetal Jadhav, M.R.Patil |
| Citation |
Vol. 16 No. 2 pp. 98-100 |
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Abstract |
Crowdsourcing is an act of outsourcing tasks, traditionally performed by an employee or contractor, which are now performed by a large group of people. Recent survey deals with the problem of evaluating the submissions to crowdsourcing websites on which data is increasing rapidly in both volume and complexity. Thus, with an increasing number of submissions, the process of rate submissions, select winners and adjust monetary rewards is getting more complex, time consuming and hence more expensive. To overcome this problem text mining methodology can be used which consist of series of operations like Data extraction, pre-processing tf-idf calculation, calculating similarity and clustering and finally cluster submission. But results using these operations in existing methodology also show that this aspect does not do the entire trick of evaluating submissions. Hence propose methodology uses classification using Apriori algorithm which will find relations of clustered terms. |
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Keywords |
Crowdsourcing, Clustering, Information Retrieval, Classification, Pre-processing. |
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